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train_transfer_learning.tex
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\documentclass[11pt]{article}
\usepackage[breakable]{tcolorbox}
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% Basic figure setup, for now with no caption control since it's done
% automatically by Pandoc (which extracts  syntax from Markdown).
\usepackage{graphicx}
% Maintain compatibility with old templates. Remove in nbconvert 6.0
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% Ensure that by default, figures have no caption (until we provide a
% proper Figure object with a Caption API and a way to capture that
% in the conversion process - todo).
\usepackage{caption}
\DeclareCaptionFormat{nocaption}{}
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\usepackage{geometry} % Used to adjust the document margins
\usepackage{amsmath} % Equations
\usepackage{amssymb} % Equations
\usepackage{textcomp} % defines textquotesingle
% Hack from http://tex.stackexchange.com/a/47451/13684:
\AtBeginDocument{%
\def\PYZsq{\textquotesingle}% Upright quotes in Pygmentized code
}
\usepackage{upquote} % Upright quotes for verbatim code
\usepackage{eurosym} % defines \euro
\usepackage[mathletters]{ucs} % Extended unicode (utf-8) support
\usepackage{fancyvrb} % verbatim replacement that allows latex
\usepackage{grffile} % extends the file name processing of package graphics
% to support a larger range
\makeatletter % fix for grffile with XeLaTeX
\def\Gread@@xetex#1{%
\IfFileExists{"\Gin@base".bb}%
{\Gread@eps{\[email protected]}}%
{\Gread@@xetex@aux#1}%
}
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% The hyperref package gives us a pdf with properly built
% internal navigation ('pdf bookmarks' for the table of contents,
% internal cross-reference links, web links for URLs, etc.)
\usepackage{hyperref}
% The default LaTeX title has an obnoxious amount of whitespace. By default,
% titling removes some of it. It also provides customization options.
\usepackage{titling}
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\usepackage{booktabs} % table support for pandoc > 1.12.2
\usepackage[inline]{enumitem} % IRkernel/repr support (it uses the enumerate* environment)
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% Document parameters
% Document title
\title{train\_transfer\_learning}
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\expandafter\def\csname PY@tok@ch\endcsname{\let\PY@it=\textit\def\PY@tc##1{\textcolor[rgb]{0.25,0.50,0.50}{##1}}}
\expandafter\def\csname PY@tok@cm\endcsname{\let\PY@it=\textit\def\PY@tc##1{\textcolor[rgb]{0.25,0.50,0.50}{##1}}}
\expandafter\def\csname PY@tok@cpf\endcsname{\let\PY@it=\textit\def\PY@tc##1{\textcolor[rgb]{0.25,0.50,0.50}{##1}}}
\expandafter\def\csname PY@tok@c1\endcsname{\let\PY@it=\textit\def\PY@tc##1{\textcolor[rgb]{0.25,0.50,0.50}{##1}}}
\expandafter\def\csname PY@tok@cs\endcsname{\let\PY@it=\textit\def\PY@tc##1{\textcolor[rgb]{0.25,0.50,0.50}{##1}}}
\def\PYZbs{\char`\\}
\def\PYZus{\char`\_}
\def\PYZob{\char`\{}
\def\PYZcb{\char`\}}
\def\PYZca{\char`\^}
\def\PYZam{\char`\&}
\def\PYZlt{\char`\<}
\def\PYZgt{\char`\>}
\def\PYZsh{\char`\#}
\def\PYZpc{\char`\%}
\def\PYZdl{\char`\$}
\def\PYZhy{\char`\-}
\def\PYZsq{\char`\'}
\def\PYZdq{\char`\"}
\def\PYZti{\char`\~}
% for compatibility with earlier versions
\def\PYZat{@}
\def\PYZlb{[}
\def\PYZrb{]}
\makeatother
% For linebreaks inside Verbatim environment from package fancyvrb.
\makeatletter
\newbox\Wrappedcontinuationbox
\newbox\Wrappedvisiblespacebox
\newcommand*\Wrappedvisiblespace {\textcolor{red}{\textvisiblespace}}
\newcommand*\Wrappedcontinuationsymbol {\textcolor{red}{\llap{\tiny$\m@th\hookrightarrow$}}}
\newcommand*\Wrappedcontinuationindent {3ex }
\newcommand*\Wrappedafterbreak {\kern\Wrappedcontinuationindent\copy\Wrappedcontinuationbox}
% Take advantage of the already applied Pygments mark-up to insert
% potential linebreaks for TeX processing.
% {, <, #, %, $, ' and ": go to next line.
% _, }, ^, &, >, - and ~: stay at end of broken line.
% Use of \textquotesingle for straight quote.
\newcommand*\Wrappedbreaksatspecials {%
\def\PYGZus{\discretionary{\char`\_}{\Wrappedafterbreak}{\char`\_}}%
\def\PYGZob{\discretionary{}{\Wrappedafterbreak\char`\{}{\char`\{}}%
\def\PYGZcb{\discretionary{\char`\}}{\Wrappedafterbreak}{\char`\}}}%
\def\PYGZca{\discretionary{\char`\^}{\Wrappedafterbreak}{\char`\^}}%
\def\PYGZam{\discretionary{\char`\&}{\Wrappedafterbreak}{\char`\&}}%
\def\PYGZlt{\discretionary{}{\Wrappedafterbreak\char`\<}{\char`\<}}%
\def\PYGZgt{\discretionary{\char`\>}{\Wrappedafterbreak}{\char`\>}}%
\def\PYGZsh{\discretionary{}{\Wrappedafterbreak\char`\#}{\char`\#}}%
\def\PYGZpc{\discretionary{}{\Wrappedafterbreak\char`\%}{\char`\%}}%
\def\PYGZdl{\discretionary{}{\Wrappedafterbreak\char`\$}{\char`\$}}%
\def\PYGZhy{\discretionary{\char`\-}{\Wrappedafterbreak}{\char`\-}}%
\def\PYGZsq{\discretionary{}{\Wrappedafterbreak\textquotesingle}{\textquotesingle}}%
\def\PYGZdq{\discretionary{}{\Wrappedafterbreak\char`\"}{\char`\"}}%
\def\PYGZti{\discretionary{\char`\~}{\Wrappedafterbreak}{\char`\~}}%
}
% Some characters . , ; ? ! / are not pygmentized.
% This macro makes them "active" and they will insert potential linebreaks
\newcommand*\Wrappedbreaksatpunct {%
\lccode`\~`\.\lowercase{\def~}{\discretionary{\hbox{\char`\.}}{\Wrappedafterbreak}{\hbox{\char`\.}}}%
\lccode`\~`\,\lowercase{\def~}{\discretionary{\hbox{\char`\,}}{\Wrappedafterbreak}{\hbox{\char`\,}}}%
\lccode`\~`\;\lowercase{\def~}{\discretionary{\hbox{\char`\;}}{\Wrappedafterbreak}{\hbox{\char`\;}}}%
\lccode`\~`\:\lowercase{\def~}{\discretionary{\hbox{\char`\:}}{\Wrappedafterbreak}{\hbox{\char`\:}}}%
\lccode`\~`\?\lowercase{\def~}{\discretionary{\hbox{\char`\?}}{\Wrappedafterbreak}{\hbox{\char`\?}}}%
\lccode`\~`\!\lowercase{\def~}{\discretionary{\hbox{\char`\!}}{\Wrappedafterbreak}{\hbox{\char`\!}}}%
\lccode`\~`\/\lowercase{\def~}{\discretionary{\hbox{\char`\/}}{\Wrappedafterbreak}{\hbox{\char`\/}}}%
\catcode`\.\active
\catcode`\,\active
\catcode`\;\active
\catcode`\:\active
\catcode`\?\active
\catcode`\!\active
\catcode`\/\active
\lccode`\~`\~
}
\makeatother
\let\OriginalVerbatim=\Verbatim
\makeatletter
\renewcommand{\Verbatim}[1][1]{%
%\parskip\z@skip
\sbox\Wrappedcontinuationbox {\Wrappedcontinuationsymbol}%
\sbox\Wrappedvisiblespacebox {\FV@SetupFont\Wrappedvisiblespace}%
\def\FancyVerbFormatLine ##1{\hsize\linewidth
\vtop{\raggedright\hyphenpenalty\z@\exhyphenpenalty\z@
\doublehyphendemerits\z@\finalhyphendemerits\z@
\strut ##1\strut}%
}%
% If the linebreak is at a space, the latter will be displayed as visible
% space at end of first line, and a continuation symbol starts next line.
% Stretch/shrink are however usually zero for typewriter font.
\def\FV@Space {%
\nobreak\hskip\z@ plus\fontdimen3\font minus\fontdimen4\font
\discretionary{\copy\Wrappedvisiblespacebox}{\Wrappedafterbreak}
{\kern\fontdimen2\font}%
}%
% Allow breaks at special characters using \PYG... macros.
\Wrappedbreaksatspecials
% Breaks at punctuation characters . , ; ? ! and / need catcode=\active
\OriginalVerbatim[#1,codes*=\Wrappedbreaksatpunct]%
}
\makeatother
% Exact colors from NB
\definecolor{incolor}{HTML}{303F9F}
\definecolor{outcolor}{HTML}{D84315}
\definecolor{cellborder}{HTML}{CFCFCF}
\definecolor{cellbackground}{HTML}{F7F7F7}
% prompt
\makeatletter
\newcommand{\boxspacing}{\kern\kvtcb@left@rule\kern\kvtcb@boxsep}
\makeatother
\newcommand{\prompt}[4]{
\ttfamily\llap{{\color{#2}[#3]:\hspace{3pt}#4}}\vspace{-\baselineskip}
}
% Prevent overflowing lines due to hard-to-break entities
\sloppy
% Setup hyperref package
\hypersetup{
breaklinks=true, % so long urls are correctly broken across lines
colorlinks=true,
urlcolor=urlcolor,
linkcolor=linkcolor,
citecolor=citecolor,
}
% Slightly bigger margins than the latex defaults
\geometry{verbose,tmargin=1in,bmargin=1in,lmargin=1in,rmargin=1in}
\begin{document}
\maketitle
\begin{tcolorbox}[breakable, size=fbox, boxrule=1pt, pad at break*=1mm,colback=cellbackground, colframe=cellborder]
\prompt{In}{incolor}{ }{\boxspacing}
\begin{Verbatim}[commandchars=\\\{\}]
\PY{k+kn}{from} \PY{n+nn}{keras}\PY{n+nn}{.}\PY{n+nn}{layers} \PY{k+kn}{import} \PY{n}{Input}\PY{p}{,} \PY{n}{Dense}\PY{p}{,} \PY{n}{Conv2D}\PY{p}{,} \PY{n}{MaxPool2D}\PY{p}{,} \PY{n}{Flatten}\PY{p}{,} \PY{n}{Dropout}\PY{p}{,} \PY{n}{BatchNormalization}\PY{p}{,} \PY{n}{Activation}\PY{p}{,} \PY{n}{Add}
\PY{k+kn}{from} \PY{n+nn}{keras}\PY{n+nn}{.}\PY{n+nn}{optimizers} \PY{k+kn}{import} \PY{n}{Adam}
\PY{k+kn}{from} \PY{n+nn}{keras}\PY{n+nn}{.}\PY{n+nn}{models} \PY{k+kn}{import} \PY{n}{Model}
\PY{k+kn}{from} \PY{n+nn}{keras}\PY{n+nn}{.}\PY{n+nn}{callbacks} \PY{k+kn}{import} \PY{n}{ModelCheckpoint}\PY{p}{,} \PY{n}{EarlyStopping}
\PY{k+kn}{import} \PY{n+nn}{keras}
\PY{k+kn}{import} \PY{n+nn}{matplotlib}\PY{n+nn}{.}\PY{n+nn}{pyplot} \PY{k}{as} \PY{n+nn}{plt}
\PY{k+kn}{import} \PY{n+nn}{numpy} \PY{k}{as} \PY{n+nn}{np}
\PY{k+kn}{from} \PY{n+nn}{sklearn}\PY{n+nn}{.}\PY{n+nn}{model\PYZus{}selection} \PY{k+kn}{import} \PY{n}{train\PYZus{}test\PYZus{}split}
\PY{k+kn}{from} \PY{n+nn}{keras}\PY{n+nn}{.}\PY{n+nn}{preprocessing}\PY{n+nn}{.}\PY{n+nn}{image} \PY{k+kn}{import} \PY{n}{ImageDataGenerator}
\PY{k+kn}{from} \PY{n+nn}{keras}\PY{n+nn}{.}\PY{n+nn}{applications}\PY{n+nn}{.}\PY{n+nn}{resnet50} \PY{k+kn}{import} \PY{n}{preprocess\PYZus{}input}
\PY{k+kn}{from} \PY{n+nn}{keras}\PY{n+nn}{.}\PY{n+nn}{applications}\PY{n+nn}{.}\PY{n+nn}{resnet} \PY{k+kn}{import} \PY{n}{ResNet50} \PY{k}{as} \PY{n}{resnet50}
\PY{k+kn}{import} \PY{n+nn}{os}
\PY{k+kn}{from} \PY{n+nn}{tqdm} \PY{k+kn}{import} \PY{n}{tqdm}
\PY{k+kn}{import} \PY{n+nn}{json}
\PY{k+kn}{import} \PY{n+nn}{glob}
\end{Verbatim}
\end{tcolorbox}
\begin{tcolorbox}[breakable, size=fbox, boxrule=1pt, pad at break*=1mm,colback=cellbackground, colframe=cellborder]
\prompt{In}{incolor}{ }{\boxspacing}
\begin{Verbatim}[commandchars=\\\{\}]
\PY{k+kn}{import} \PY{n+nn}{tensorflow} \PY{k}{as} \PY{n+nn}{tf}
\PY{n}{gpus}\PY{o}{=} \PY{n}{tf}\PY{o}{.}\PY{n}{config}\PY{o}{.}\PY{n}{experimental}\PY{o}{.}\PY{n}{list\PYZus{}physical\PYZus{}devices}\PY{p}{(}\PY{l+s+s1}{\PYZsq{}}\PY{l+s+s1}{GPU}\PY{l+s+s1}{\PYZsq{}}\PY{p}{)}
\PY{n}{tf}\PY{o}{.}\PY{n}{config}\PY{o}{.}\PY{n}{experimental}\PY{o}{.}\PY{n}{set\PYZus{}memory\PYZus{}growth}\PY{p}{(}\PY{n}{gpus}\PY{p}{[}\PY{l+m+mi}{0}\PY{p}{]}\PY{p}{,} \PY{k+kc}{True}\PY{p}{)}
\end{Verbatim}
\end{tcolorbox}
\begin{tcolorbox}[breakable, size=fbox, boxrule=1pt, pad at break*=1mm,colback=cellbackground, colframe=cellborder]
\prompt{In}{incolor}{ }{\boxspacing}
\begin{Verbatim}[commandchars=\\\{\}]
\PY{k}{def} \PY{n+nf}{resnet50\PYZus{}conv}\PY{p}{(}\PY{n}{shape}\PY{p}{)}\PY{p}{:}
\PY{l+s+sd}{\PYZsq{}\PYZsq{}\PYZsq{}}
\PY{l+s+sd}{ Load Resnet convolutional layers\PYZsq{} and set the input image shape of network.}
\PY{l+s+sd}{ }
\PY{l+s+sd}{ =======================================================================================}
\PY{l+s+sd}{ }
\PY{l+s+sd}{ input: A tupe containing 3 dimensions with input shape (H,W,C) RGB.}
\PY{l+s+sd}{ }
\PY{l+s+sd}{ returns: Model with convolutional layers only.}
\PY{l+s+sd}{ \PYZsq{}\PYZsq{}\PYZsq{}}
\PY{n}{input\PYZus{}tensor} \PY{o}{=} \PY{n}{Input}\PY{p}{(}\PY{n}{shape}\PY{o}{=}\PY{n}{shape}\PY{p}{)}
\PY{n}{resnet\PYZus{}model\PYZus{}top} \PY{o}{=} \PY{n}{resnet50}\PY{p}{(}\PY{n}{include\PYZus{}top}\PY{o}{=}\PY{k+kc}{True}\PY{p}{,} \PY{n}{weights}\PY{o}{=}\PY{l+s+s1}{\PYZsq{}}\PY{l+s+s1}{imagenet}\PY{l+s+s1}{\PYZsq{}}\PY{p}{,} \PY{n}{input\PYZus{}tensor}\PY{o}{=}\PY{n}{input\PYZus{}tensor}\PY{p}{)}
\PY{n}{resnet\PYZus{}model\PYZus{}top}\PY{o}{.}\PY{n}{summary}\PY{p}{(}\PY{p}{)}
\PY{k}{return} \PY{n}{resnet\PYZus{}model\PYZus{}top}
\end{Verbatim}
\end{tcolorbox}
\begin{tcolorbox}[breakable, size=fbox, boxrule=1pt, pad at break*=1mm,colback=cellbackground, colframe=cellborder]
\prompt{In}{incolor}{ }{\boxspacing}
\begin{Verbatim}[commandchars=\\\{\}]
\PY{c+c1}{\PYZsh{} Defines input shape and gets resnet50v1 backbone}
\PY{n}{input\PYZus{}shape} \PY{o}{=} \PY{p}{(}\PY{l+m+mi}{224}\PY{p}{,}\PY{l+m+mi}{224}\PY{p}{,} \PY{l+m+mi}{3}\PY{p}{)}
\PY{p}{(}\PY{n}{w}\PY{p}{,} \PY{n}{h}\PY{p}{,} \PY{n}{\PYZus{}}\PY{p}{)} \PY{o}{=} \PY{n}{input\PYZus{}shape}
\PY{n}{net} \PY{o}{=} \PY{n}{resnet50\PYZus{}conv}\PY{p}{(}\PY{n}{input\PYZus{}shape}\PY{p}{)}
\end{Verbatim}
\end{tcolorbox}
\begin{tcolorbox}[breakable, size=fbox, boxrule=1pt, pad at break*=1mm,colback=cellbackground, colframe=cellborder]
\prompt{In}{incolor}{ }{\boxspacing}
\begin{Verbatim}[commandchars=\\\{\}]
\PY{c+c1}{\PYZsh{} Helps to see the name and position of each layer.}
\PY{n}{lay\PYZus{}nb} \PY{o}{=} \PY{l+m+mi}{0}
\PY{k}{for} \PY{n}{layer} \PY{o+ow}{in} \PY{n}{net}\PY{o}{.}\PY{n}{layers}\PY{p}{:}
\PY{c+c1}{\PYZsh{}print(layer)}
\PY{n+nb}{print}\PY{p}{(}\PY{n}{layer}\PY{o}{.}\PY{n}{name}\PY{p}{)}
\PY{c+c1}{\PYZsh{}print(layer.output)}
\PY{n}{lay\PYZus{}nb} \PY{o}{+}\PY{o}{=} \PY{l+m+mi}{1}
\PY{n}{lay\PYZus{}name} \PY{o}{=} \PY{n}{layer}\PY{o}{.}\PY{n}{name}
\PY{c+c1}{\PYZsh{} if layer.name == \PYZsq{}conv4\PYZus{}block6\PYZus{}out\PYZsq{}:}
\PY{c+c1}{\PYZsh{} break}
\PY{k}{if} \PY{n}{layer}\PY{o}{.}\PY{n}{name} \PY{o}{==} \PY{l+s+s1}{\PYZsq{}}\PY{l+s+s1}{avg\PYZus{}pool}\PY{l+s+s1}{\PYZsq{}}\PY{p}{:}
\PY{k}{break}
\PY{n+nb}{print}\PY{p}{(}\PY{n}{lay\PYZus{}nb}\PY{p}{)}
\PY{n+nb}{print}\PY{p}{(}\PY{n}{lay\PYZus{}name}\PY{p}{)}
\end{Verbatim}
\end{tcolorbox}
\begin{tcolorbox}[breakable, size=fbox, boxrule=1pt, pad at break*=1mm,colback=cellbackground, colframe=cellborder]
\prompt{In}{incolor}{ }{\boxspacing}
\begin{Verbatim}[commandchars=\\\{\}]
\PY{k}{def} \PY{n+nf}{create\PYZus{}custom\PYZus{}model}\PY{p}{(}\PY{n}{net}\PY{p}{,} \PY{n}{optm}\PY{p}{,} \PY{n}{classes}\PY{p}{,} \PY{n}{questao6}\PY{p}{)}\PY{p}{:}
\PY{l+s+sd}{\PYZsq{}\PYZsq{}\PYZsq{}}
\PY{l+s+sd}{ Fine tunning implementation according to exercise 5 and 6.}
\PY{l+s+sd}{ }
\PY{l+s+sd}{ =======================================================================================}
\PY{l+s+sd}{ }
\PY{l+s+sd}{ net: Resnet50 pre\PYZhy{}trained model}
\PY{l+s+sd}{ }
\PY{l+s+sd}{ optm: Optmizer used to train the network.}
\PY{l+s+sd}{ }
\PY{l+s+sd}{ classes: Number of classes in dataset.}
\PY{l+s+sd}{ }
\PY{l+s+sd}{ questao6: If wants to implement the Exercise 5 implementation put the flag to False. Othewise,}
\PY{l+s+sd}{ It will implement exercise 6 with custom fully\PYZhy{}connected layers and another convolutional block.}
\PY{l+s+sd}{ }
\PY{l+s+sd}{ }
\PY{l+s+sd}{ returns: Model compiled.}
\PY{l+s+sd}{ \PYZsq{}\PYZsq{}\PYZsq{}}
\PY{c+c1}{\PYZsh{} Gets the average pooling layer.}
\PY{n}{x} \PY{o}{=} \PY{n}{net}\PY{o}{.}\PY{n}{layers}\PY{p}{[}\PY{o}{\PYZhy{}}\PY{l+m+mi}{2}\PY{p}{]}\PY{o}{.}\PY{n}{output}
\PY{c+c1}{\PYZsh{} flatten + fully\PYZhy{}connected + softmax activation}
\PY{k}{if}\PY{p}{(}\PY{n}{questao6} \PY{o}{==} \PY{k+kc}{True}\PY{p}{)}\PY{p}{:}
\PY{n}{x} \PY{o}{=} \PY{n}{Dense}\PY{p}{(}\PY{l+m+mi}{1024}\PY{p}{,} \PY{n}{activation}\PY{o}{=}\PY{l+s+s1}{\PYZsq{}}\PY{l+s+s1}{relu}\PY{l+s+s1}{\PYZsq{}}\PY{p}{)}\PY{p}{(}\PY{n}{x}\PY{p}{)}
\PY{n}{x} \PY{o}{=} \PY{n}{Dense}\PY{p}{(}\PY{l+m+mi}{1024}\PY{p}{,} \PY{n}{activation}\PY{o}{=}\PY{l+s+s1}{\PYZsq{}}\PY{l+s+s1}{relu}\PY{l+s+s1}{\PYZsq{}}\PY{p}{)}\PY{p}{(}\PY{n}{x}\PY{p}{)}
\PY{n}{x} \PY{o}{=} \PY{n}{Dense}\PY{p}{(}\PY{l+m+mi}{1024}\PY{p}{,} \PY{n}{activation}\PY{o}{=}\PY{l+s+s1}{\PYZsq{}}\PY{l+s+s1}{relu}\PY{l+s+s1}{\PYZsq{}}\PY{p}{)}\PY{p}{(}\PY{n}{x}\PY{p}{)}
\PY{n}{x} \PY{o}{=} \PY{n}{Dropout}\PY{p}{(}\PY{l+m+mf}{0.25}\PY{p}{)}\PY{p}{(}\PY{n}{x}\PY{p}{)}
\PY{n}{x} \PY{o}{=} \PY{n}{Dense}\PY{p}{(}\PY{n}{classes}\PY{p}{,} \PY{n}{activation}\PY{o}{=}\PY{l+s+s1}{\PYZsq{}}\PY{l+s+s1}{softmax}\PY{l+s+s1}{\PYZsq{}}\PY{p}{)}\PY{p}{(}\PY{n}{x}\PY{p}{)}
\PY{n}{custom\PYZus{}model} \PY{o}{=} \PY{n}{Model}\PY{p}{(}\PY{n}{net}\PY{o}{.}\PY{n}{input}\PY{p}{,}\PY{n}{x}\PY{p}{)}
\PY{c+c1}{\PYZsh{} Froze layers}
\PY{k}{for} \PY{n}{layer} \PY{o+ow}{in} \PY{n}{custom\PYZus{}model}\PY{o}{.}\PY{n}{layers}\PY{p}{[}\PY{p}{:}\PY{l+m+mi}{176}\PY{p}{]}\PY{p}{:}
\PY{k}{if}\PY{p}{(} \PY{l+s+s2}{\PYZdq{}}\PY{l+s+s2}{conv5\PYZus{}block3}\PY{l+s+s2}{\PYZdq{}} \PY{o+ow}{in} \PY{n}{layer}\PY{o}{.}\PY{n}{name} \PY{o+ow}{or} \PY{l+s+s2}{\PYZdq{}}\PY{l+s+s2}{avg\PYZus{}pool}\PY{l+s+s2}{\PYZdq{}} \PY{o+ow}{in} \PY{n}{layer}\PY{o}{.}\PY{n}{name}\PY{p}{)}\PY{p}{:}
\PY{n}{layer}\PY{o}{.}\PY{n}{trainable} \PY{o}{=} \PY{k+kc}{True}
\PY{k}{else}\PY{p}{:}
\PY{n}{layer}\PY{o}{.}\PY{n}{trainable} \PY{o}{=} \PY{k+kc}{False}
\PY{k}{if}\PY{p}{(}\PY{n}{questao6} \PY{o}{==} \PY{k+kc}{True}\PY{p}{)}\PY{p}{:}
\PY{k}{if}\PY{p}{(} \PY{l+s+s2}{\PYZdq{}}\PY{l+s+s2}{conv5\PYZus{}block2}\PY{l+s+s2}{\PYZdq{}} \PY{o+ow}{in} \PY{n}{layer}\PY{o}{.}\PY{n}{name}\PY{p}{)}\PY{p}{:}
\PY{n}{layer}\PY{o}{.}\PY{n}{trainable} \PY{o}{=} \PY{k+kc}{True}
\PY{c+c1}{\PYZsh{} Compile it}
\PY{n}{custom\PYZus{}model}\PY{o}{.}\PY{n}{compile}\PY{p}{(}\PY{n}{loss}\PY{o}{=}\PY{l+s+s1}{\PYZsq{}}\PY{l+s+s1}{categorical\PYZus{}crossentropy}\PY{l+s+s1}{\PYZsq{}}\PY{p}{,}
\PY{n}{optimizer}\PY{o}{=}\PY{n}{optm}\PY{p}{,}
\PY{n}{metrics}\PY{o}{=}\PY{p}{[}\PY{l+s+s1}{\PYZsq{}}\PY{l+s+s1}{accuracy}\PY{l+s+s1}{\PYZsq{}}\PY{p}{]}\PY{p}{)}
\PY{k}{return} \PY{n}{custom\PYZus{}model}
\end{Verbatim}
\end{tcolorbox}
\begin{tcolorbox}[breakable, size=fbox, boxrule=1pt, pad at break*=1mm,colback=cellbackground, colframe=cellborder]
\prompt{In}{incolor}{ }{\boxspacing}
\begin{Verbatim}[commandchars=\\\{\}]
\PY{k}{def} \PY{n+nf}{create\PYZus{}custom\PYZus{}model\PYZus{}q7}\PY{p}{(}\PY{n}{net}\PY{p}{,} \PY{n}{optm}\PY{p}{,} \PY{n}{classes}\PY{p}{)}\PY{p}{:}
\PY{l+s+sd}{\PYZsq{}\PYZsq{}\PYZsq{}}
\PY{l+s+sd}{ Fine tunning implementation according to exercise 7. convolutional layer 5 is implemented from}
\PY{l+s+sd}{ scratch. Other layers before convolutional layer 5 are frozen. }
\PY{l+s+sd}{ Custom dense layers are implemented also.}
\PY{l+s+sd}{ }
\PY{l+s+sd}{ =======================================================================================}
\PY{l+s+sd}{ }
\PY{l+s+sd}{ net: Resnet50 pre\PYZhy{}trained model}
\PY{l+s+sd}{ }
\PY{l+s+sd}{ optm: Optmizer used to train the network.}
\PY{l+s+sd}{ }
\PY{l+s+sd}{ classes: Number of classes in dataset.}
\PY{l+s+sd}{ }
\PY{l+s+sd}{ returns: Model compiled.}
\PY{l+s+sd}{ \PYZsq{}\PYZsq{}\PYZsq{}}
\PY{n}{layer\PYZus{}dict} \PY{o}{=} \PY{n+nb}{dict}\PY{p}{(}\PY{p}{[}\PY{p}{(}\PY{n}{layer}\PY{o}{.}\PY{n}{name}\PY{p}{,} \PY{n}{layer}\PY{p}{)} \PY{k}{for} \PY{n}{layer} \PY{o+ow}{in} \PY{n}{net}\PY{o}{.}\PY{n}{layers}\PY{p}{]}\PY{p}{)}
\PY{n}{conv4\PYZus{}block6\PYZus{}out} \PY{o}{=} \PY{n}{layer\PYZus{}dict}\PY{p}{[}\PY{l+s+s1}{\PYZsq{}}\PY{l+s+s1}{conv4\PYZus{}block6\PYZus{}out}\PY{l+s+s1}{\PYZsq{}}\PY{p}{]}\PY{o}{.}\PY{n}{output}
\PY{c+c1}{\PYZsh{} Custom Convolutional layers}
\PY{c+c1}{\PYZsh{} custom\PYZus{}conv\PYZus{}block1}
\PY{n}{momemtum}\PY{o}{=}\PY{l+m+mf}{0.8}
\PY{n}{activation\PYZus{}f} \PY{o}{=} \PY{l+s+s1}{\PYZsq{}}\PY{l+s+s1}{relu}\PY{l+s+s1}{\PYZsq{}}
\PY{c+c1}{\PYZsh{} conv\PYZus{}block\PYZus{}1\PYZus{}1}
\PY{n}{x} \PY{o}{=} \PY{n}{Conv2D}\PY{p}{(}\PY{l+m+mi}{512}\PY{p}{,} \PY{p}{(}\PY{l+m+mi}{1}\PY{p}{,}\PY{l+m+mi}{1}\PY{p}{)}\PY{p}{,} \PY{n}{strides}\PY{o}{=}\PY{l+m+mi}{1}\PY{p}{,} \PY{n}{activation}\PY{o}{=}\PY{l+s+s1}{\PYZsq{}}\PY{l+s+s1}{linear}\PY{l+s+s1}{\PYZsq{}}\PY{p}{,} \PY{n}{padding}\PY{o}{=}\PY{l+s+s1}{\PYZsq{}}\PY{l+s+s1}{same}\PY{l+s+s1}{\PYZsq{}}\PY{p}{)}\PY{p}{(}\PY{n}{conv4\PYZus{}block6\PYZus{}out}\PY{p}{)}
\PY{n}{x} \PY{o}{=} \PY{n}{BatchNormalization}\PY{p}{(}\PY{n}{momentum}\PY{o}{=}\PY{n}{momemtum}\PY{p}{)}\PY{p}{(}\PY{n}{x}\PY{p}{)}
\PY{n}{x} \PY{o}{=} \PY{n}{Activation}\PY{p}{(}\PY{n}{activation\PYZus{}f}\PY{p}{)}\PY{p}{(}\PY{n}{x}\PY{p}{)}
\PY{c+c1}{\PYZsh{} conv\PYZus{}block\PYZus{}1\PYZus{}2}
\PY{n}{x} \PY{o}{=} \PY{n}{Conv2D}\PY{p}{(}\PY{l+m+mi}{512}\PY{p}{,} \PY{p}{(}\PY{l+m+mi}{3}\PY{p}{,}\PY{l+m+mi}{3}\PY{p}{)}\PY{p}{,} \PY{n}{strides}\PY{o}{=}\PY{l+m+mi}{1}\PY{p}{,} \PY{n}{activation}\PY{o}{=}\PY{l+s+s1}{\PYZsq{}}\PY{l+s+s1}{linear}\PY{l+s+s1}{\PYZsq{}}\PY{p}{,} \PY{n}{padding}\PY{o}{=}\PY{l+s+s1}{\PYZsq{}}\PY{l+s+s1}{same}\PY{l+s+s1}{\PYZsq{}}\PY{p}{)}\PY{p}{(}\PY{n}{x}\PY{p}{)}
\PY{n}{x} \PY{o}{=} \PY{n}{BatchNormalization}\PY{p}{(}\PY{n}{momentum}\PY{o}{=}\PY{n}{momemtum}\PY{p}{)}\PY{p}{(}\PY{n}{x}\PY{p}{)}
\PY{n}{x} \PY{o}{=} \PY{n}{Activation}\PY{p}{(}\PY{n}{activation\PYZus{}f}\PY{p}{)}\PY{p}{(}\PY{n}{x}\PY{p}{)}
\PY{c+c1}{\PYZsh{} conv\PYZus{}block\PYZus{}1\PYZus{}0}
\PY{n}{y} \PY{o}{=} \PY{n}{Conv2D}\PY{p}{(}\PY{l+m+mi}{2048}\PY{p}{,} \PY{p}{(}\PY{l+m+mi}{1}\PY{p}{,}\PY{l+m+mi}{1}\PY{p}{)}\PY{p}{,} \PY{n}{strides}\PY{o}{=}\PY{l+m+mi}{1}\PY{p}{,} \PY{n}{activation}\PY{o}{=}\PY{l+s+s1}{\PYZsq{}}\PY{l+s+s1}{linear}\PY{l+s+s1}{\PYZsq{}}\PY{p}{,} \PY{n}{padding}\PY{o}{=}\PY{l+s+s1}{\PYZsq{}}\PY{l+s+s1}{same}\PY{l+s+s1}{\PYZsq{}}\PY{p}{)}\PY{p}{(}\PY{n}{conv4\PYZus{}block6\PYZus{}out}\PY{p}{)}
\PY{n}{y} \PY{o}{=} \PY{n}{BatchNormalization}\PY{p}{(}\PY{n}{momentum}\PY{o}{=}\PY{n}{momemtum}\PY{p}{)}\PY{p}{(}\PY{n}{y}\PY{p}{)}
\PY{c+c1}{\PYZsh{} conv\PYZus{}block\PYZus{}1\PYZus{}3}
\PY{n}{x} \PY{o}{=} \PY{n}{Conv2D}\PY{p}{(}\PY{l+m+mi}{2048}\PY{p}{,} \PY{p}{(}\PY{l+m+mi}{1}\PY{p}{,}\PY{l+m+mi}{1}\PY{p}{)}\PY{p}{,} \PY{n}{strides}\PY{o}{=}\PY{l+m+mi}{1}\PY{p}{,} \PY{n}{activation}\PY{o}{=}\PY{l+s+s1}{\PYZsq{}}\PY{l+s+s1}{linear}\PY{l+s+s1}{\PYZsq{}}\PY{p}{,} \PY{n}{padding}\PY{o}{=}\PY{l+s+s1}{\PYZsq{}}\PY{l+s+s1}{same}\PY{l+s+s1}{\PYZsq{}}\PY{p}{)}\PY{p}{(}\PY{n}{x}\PY{p}{)}
\PY{n}{x} \PY{o}{=} \PY{n}{BatchNormalization}\PY{p}{(}\PY{n}{momentum}\PY{o}{=}\PY{n}{momemtum}\PY{p}{)}\PY{p}{(}\PY{n}{x}\PY{p}{)}
\PY{n}{x} \PY{o}{=} \PY{n}{Add}\PY{p}{(}\PY{p}{)}\PY{p}{(}\PY{p}{[}\PY{n}{y}\PY{p}{,} \PY{n}{x}\PY{p}{]}\PY{p}{)}
\PY{n}{custom\PYZus{}conv\PYZus{}block1\PYZus{}out} \PY{o}{=} \PY{n}{Activation}\PY{p}{(}\PY{n}{activation\PYZus{}f}\PY{p}{)}\PY{p}{(}\PY{n}{x}\PY{p}{)}
\PY{c+c1}{\PYZsh{} custom\PYZus{}conv\PYZus{}block2}
\PY{n}{x} \PY{o}{=} \PY{n}{Conv2D}\PY{p}{(}\PY{l+m+mi}{512}\PY{p}{,} \PY{p}{(}\PY{l+m+mi}{1}\PY{p}{,}\PY{l+m+mi}{1}\PY{p}{)}\PY{p}{,} \PY{n}{strides}\PY{o}{=}\PY{l+m+mi}{1}\PY{p}{,} \PY{n}{activation}\PY{o}{=}\PY{l+s+s1}{\PYZsq{}}\PY{l+s+s1}{linear}\PY{l+s+s1}{\PYZsq{}}\PY{p}{,} \PY{n}{padding}\PY{o}{=}\PY{l+s+s1}{\PYZsq{}}\PY{l+s+s1}{same}\PY{l+s+s1}{\PYZsq{}}\PY{p}{)}\PY{p}{(}\PY{n}{custom\PYZus{}conv\PYZus{}block1\PYZus{}out}\PY{p}{)}
\PY{n}{x} \PY{o}{=} \PY{n}{BatchNormalization}\PY{p}{(}\PY{n}{momentum}\PY{o}{=}\PY{n}{momemtum}\PY{p}{)}\PY{p}{(}\PY{n}{x}\PY{p}{)}
\PY{n}{x} \PY{o}{=} \PY{n}{Activation}\PY{p}{(}\PY{n}{activation\PYZus{}f}\PY{p}{)}\PY{p}{(}\PY{n}{x}\PY{p}{)}
\PY{n}{x} \PY{o}{=} \PY{n}{Conv2D}\PY{p}{(}\PY{l+m+mi}{512}\PY{p}{,} \PY{p}{(}\PY{l+m+mi}{3}\PY{p}{,}\PY{l+m+mi}{3}\PY{p}{)}\PY{p}{,} \PY{n}{strides}\PY{o}{=}\PY{l+m+mi}{1}\PY{p}{,} \PY{n}{activation}\PY{o}{=}\PY{l+s+s1}{\PYZsq{}}\PY{l+s+s1}{linear}\PY{l+s+s1}{\PYZsq{}}\PY{p}{,} \PY{n}{padding}\PY{o}{=}\PY{l+s+s1}{\PYZsq{}}\PY{l+s+s1}{same}\PY{l+s+s1}{\PYZsq{}}\PY{p}{)}\PY{p}{(}\PY{n}{x}\PY{p}{)}
\PY{n}{x} \PY{o}{=} \PY{n}{BatchNormalization}\PY{p}{(}\PY{n}{momentum}\PY{o}{=}\PY{n}{momemtum}\PY{p}{)}\PY{p}{(}\PY{n}{x}\PY{p}{)}
\PY{n}{x} \PY{o}{=} \PY{n}{Activation}\PY{p}{(}\PY{n}{activation\PYZus{}f}\PY{p}{)}\PY{p}{(}\PY{n}{x}\PY{p}{)}
\PY{n}{x} \PY{o}{=} \PY{n}{Conv2D}\PY{p}{(}\PY{l+m+mi}{2048}\PY{p}{,} \PY{p}{(}\PY{l+m+mi}{1}\PY{p}{,}\PY{l+m+mi}{1}\PY{p}{)}\PY{p}{,} \PY{n}{strides}\PY{o}{=}\PY{l+m+mi}{1}\PY{p}{,} \PY{n}{activation}\PY{o}{=}\PY{l+s+s1}{\PYZsq{}}\PY{l+s+s1}{linear}\PY{l+s+s1}{\PYZsq{}}\PY{p}{,} \PY{n}{padding}\PY{o}{=}\PY{l+s+s1}{\PYZsq{}}\PY{l+s+s1}{same}\PY{l+s+s1}{\PYZsq{}}\PY{p}{)}\PY{p}{(}\PY{n}{x}\PY{p}{)}
\PY{n}{x} \PY{o}{=} \PY{n}{BatchNormalization}\PY{p}{(}\PY{n}{momentum}\PY{o}{=}\PY{n}{momemtum}\PY{p}{)}\PY{p}{(}\PY{n}{x}\PY{p}{)}
\PY{n}{x} \PY{o}{=} \PY{n}{Add}\PY{p}{(}\PY{p}{)}\PY{p}{(}\PY{p}{[}\PY{n}{custom\PYZus{}conv\PYZus{}block1\PYZus{}out}\PY{p}{,} \PY{n}{x}\PY{p}{]}\PY{p}{)}
\PY{n}{custom\PYZus{}conv\PYZus{}block2\PYZus{}out} \PY{o}{=} \PY{n}{Activation}\PY{p}{(}\PY{n}{activation\PYZus{}f}\PY{p}{)}\PY{p}{(}\PY{n}{x}\PY{p}{)}
\PY{c+c1}{\PYZsh{} custom\PYZus{}conv\PYZus{}block3}
\PY{n}{x} \PY{o}{=} \PY{n}{Conv2D}\PY{p}{(}\PY{l+m+mi}{512}\PY{p}{,} \PY{p}{(}\PY{l+m+mi}{1}\PY{p}{,}\PY{l+m+mi}{1}\PY{p}{)}\PY{p}{,} \PY{n}{strides}\PY{o}{=}\PY{l+m+mi}{1}\PY{p}{,} \PY{n}{activation}\PY{o}{=}\PY{l+s+s1}{\PYZsq{}}\PY{l+s+s1}{linear}\PY{l+s+s1}{\PYZsq{}}\PY{p}{,} \PY{n}{padding}\PY{o}{=}\PY{l+s+s1}{\PYZsq{}}\PY{l+s+s1}{same}\PY{l+s+s1}{\PYZsq{}}\PY{p}{)}\PY{p}{(}\PY{n}{custom\PYZus{}conv\PYZus{}block2\PYZus{}out}\PY{p}{)}
\PY{n}{x} \PY{o}{=} \PY{n}{BatchNormalization}\PY{p}{(}\PY{n}{momentum}\PY{o}{=}\PY{n}{momemtum}\PY{p}{)}\PY{p}{(}\PY{n}{x}\PY{p}{)}
\PY{n}{x} \PY{o}{=} \PY{n}{Activation}\PY{p}{(}\PY{n}{activation\PYZus{}f}\PY{p}{)}\PY{p}{(}\PY{n}{x}\PY{p}{)}
\PY{n}{x} \PY{o}{=} \PY{n}{Conv2D}\PY{p}{(}\PY{l+m+mi}{512}\PY{p}{,} \PY{p}{(}\PY{l+m+mi}{3}\PY{p}{,}\PY{l+m+mi}{3}\PY{p}{)}\PY{p}{,} \PY{n}{strides}\PY{o}{=}\PY{l+m+mi}{1}\PY{p}{,} \PY{n}{activation}\PY{o}{=}\PY{l+s+s1}{\PYZsq{}}\PY{l+s+s1}{linear}\PY{l+s+s1}{\PYZsq{}}\PY{p}{,} \PY{n}{padding}\PY{o}{=}\PY{l+s+s1}{\PYZsq{}}\PY{l+s+s1}{same}\PY{l+s+s1}{\PYZsq{}}\PY{p}{)}\PY{p}{(}\PY{n}{x}\PY{p}{)}
\PY{n}{x} \PY{o}{=} \PY{n}{BatchNormalization}\PY{p}{(}\PY{n}{momentum}\PY{o}{=}\PY{n}{momemtum}\PY{p}{)}\PY{p}{(}\PY{n}{x}\PY{p}{)}
\PY{n}{x} \PY{o}{=} \PY{n}{Activation}\PY{p}{(}\PY{n}{activation\PYZus{}f}\PY{p}{)}\PY{p}{(}\PY{n}{x}\PY{p}{)}
\PY{n}{x} \PY{o}{=} \PY{n}{Conv2D}\PY{p}{(}\PY{l+m+mi}{2048}\PY{p}{,} \PY{p}{(}\PY{l+m+mi}{1}\PY{p}{,}\PY{l+m+mi}{1}\PY{p}{)}\PY{p}{,} \PY{n}{strides}\PY{o}{=}\PY{l+m+mi}{1}\PY{p}{,} \PY{n}{activation}\PY{o}{=}\PY{l+s+s1}{\PYZsq{}}\PY{l+s+s1}{linear}\PY{l+s+s1}{\PYZsq{}}\PY{p}{,} \PY{n}{padding}\PY{o}{=}\PY{l+s+s1}{\PYZsq{}}\PY{l+s+s1}{same}\PY{l+s+s1}{\PYZsq{}}\PY{p}{)}\PY{p}{(}\PY{n}{x}\PY{p}{)}
\PY{n}{x} \PY{o}{=} \PY{n}{BatchNormalization}\PY{p}{(}\PY{n}{momentum}\PY{o}{=}\PY{n}{momemtum}\PY{p}{)}\PY{p}{(}\PY{n}{x}\PY{p}{)}
\PY{n}{x} \PY{o}{=} \PY{n}{Add}\PY{p}{(}\PY{p}{)}\PY{p}{(}\PY{p}{[}\PY{n}{custom\PYZus{}conv\PYZus{}block2\PYZus{}out}\PY{p}{,} \PY{n}{x}\PY{p}{]}\PY{p}{)}
\PY{n}{custom\PYZus{}conv\PYZus{}block3\PYZus{}out} \PY{o}{=} \PY{n}{Activation}\PY{p}{(}\PY{n}{activation\PYZus{}f}\PY{p}{)}\PY{p}{(}\PY{n}{x}\PY{p}{)}
\PY{c+c1}{\PYZsh{}Global Aerage Pooling}
\PY{n}{x} \PY{o}{=} \PY{n}{layer\PYZus{}dict}\PY{p}{[}\PY{l+s+s1}{\PYZsq{}}\PY{l+s+s1}{avg\PYZus{}pool}\PY{l+s+s1}{\PYZsq{}}\PY{p}{]}\PY{p}{(}\PY{n}{custom\PYZus{}conv\PYZus{}block3\PYZus{}out}\PY{p}{)}
\PY{c+c1}{\PYZsh{} custom fully\PYZhy{}connected + softmax activation}
\PY{n}{x} \PY{o}{=} \PY{n}{Dense}\PY{p}{(}\PY{l+m+mi}{1024}\PY{p}{,} \PY{n}{activation}\PY{o}{=}\PY{l+s+s1}{\PYZsq{}}\PY{l+s+s1}{relu}\PY{l+s+s1}{\PYZsq{}}\PY{p}{)}\PY{p}{(}\PY{n}{x}\PY{p}{)}
\PY{n}{x} \PY{o}{=} \PY{n}{Dense}\PY{p}{(}\PY{l+m+mi}{1024}\PY{p}{,} \PY{n}{activation}\PY{o}{=}\PY{l+s+s1}{\PYZsq{}}\PY{l+s+s1}{relu}\PY{l+s+s1}{\PYZsq{}}\PY{p}{)}\PY{p}{(}\PY{n}{x}\PY{p}{)}
\PY{n}{x} \PY{o}{=} \PY{n}{Dense}\PY{p}{(}\PY{l+m+mi}{1024}\PY{p}{,} \PY{n}{activation}\PY{o}{=}\PY{l+s+s1}{\PYZsq{}}\PY{l+s+s1}{relu}\PY{l+s+s1}{\PYZsq{}}\PY{p}{)}\PY{p}{(}\PY{n}{x}\PY{p}{)}
\PY{n}{x} \PY{o}{=} \PY{n}{Dropout}\PY{p}{(}\PY{l+m+mf}{0.25}\PY{p}{)}\PY{p}{(}\PY{n}{x}\PY{p}{)}
\PY{n}{x} \PY{o}{=} \PY{n}{Dense}\PY{p}{(}\PY{n}{classes}\PY{p}{,} \PY{n}{activation}\PY{o}{=}\PY{l+s+s1}{\PYZsq{}}\PY{l+s+s1}{softmax}\PY{l+s+s1}{\PYZsq{}}\PY{p}{)}\PY{p}{(}\PY{n}{x}\PY{p}{)}
\PY{n}{custom\PYZus{}model} \PY{o}{=} \PY{n}{Model}\PY{p}{(}\PY{n}{net}\PY{o}{.}\PY{n}{input}\PY{p}{,}\PY{n}{x}\PY{p}{)}
\PY{c+c1}{\PYZsh{} Froze layers}
\PY{k}{for} \PY{n}{layer} \PY{o+ow}{in} \PY{n}{custom\PYZus{}model}\PY{o}{.}\PY{n}{layers}\PY{p}{[}\PY{p}{:}\PY{l+m+mi}{143}\PY{p}{]}\PY{p}{:}
\PY{n}{layer}\PY{o}{.}\PY{n}{trainable} \PY{o}{=} \PY{k+kc}{False}
\PY{c+c1}{\PYZsh{} Compile it}
\PY{n}{custom\PYZus{}model}\PY{o}{.}\PY{n}{compile}\PY{p}{(}\PY{n}{loss}\PY{o}{=}\PY{l+s+s1}{\PYZsq{}}\PY{l+s+s1}{categorical\PYZus{}crossentropy}\PY{l+s+s1}{\PYZsq{}}\PY{p}{,}
\PY{n}{optimizer}\PY{o}{=}\PY{n}{optm}\PY{p}{,}
\PY{n}{metrics}\PY{o}{=}\PY{p}{[}\PY{l+s+s1}{\PYZsq{}}\PY{l+s+s1}{accuracy}\PY{l+s+s1}{\PYZsq{}}\PY{p}{]}\PY{p}{)}
\PY{k}{return} \PY{n}{custom\PYZus{}model}
\end{Verbatim}
\end{tcolorbox}
\begin{tcolorbox}[breakable, size=fbox, boxrule=1pt, pad at break*=1mm,colback=cellbackground, colframe=cellborder]
\prompt{In}{incolor}{ }{\boxspacing}
\begin{Verbatim}[commandchars=\\\{\}]
\PY{n}{lr} \PY{o}{=} \PY{l+m+mf}{0.5e\PYZhy{}5}
\PY{n}{optm} \PY{o}{=} \PY{n}{Adam}\PY{p}{(}\PY{n}{learning\PYZus{}rate} \PY{o}{=} \PY{n}{lr}\PY{p}{,} \PY{n}{decay}\PY{o}{=}\PY{l+m+mf}{0.001}\PY{p}{)}
\PY{n}{classes} \PY{o}{=} \PY{l+m+mi}{5}
\PY{c+c1}{\PYZsh{}custom\PYZus{}resnet = create\PYZus{}custom\PYZus{}model(net,optm,lay\PYZus{}name,lay\PYZus{}nb,classes,questao6=False)}
\PY{n}{custom\PYZus{}resnet} \PY{o}{=} \PY{n}{create\PYZus{}custom\PYZus{}model\PYZus{}q7}\PY{p}{(}\PY{n}{net}\PY{p}{,}\PY{n}{optm}\PY{p}{,}\PY{n}{lay\PYZus{}name}\PY{p}{,}\PY{n}{lay\PYZus{}nb}\PY{p}{,}\PY{n}{classes}\PY{p}{)}
\end{Verbatim}
\end{tcolorbox}
\begin{tcolorbox}[breakable, size=fbox, boxrule=1pt, pad at break*=1mm,colback=cellbackground, colframe=cellborder]
\prompt{In}{incolor}{ }{\boxspacing}
\begin{Verbatim}[commandchars=\\\{\}]
\PY{n}{custom\PYZus{}resnet}\PY{o}{.}\PY{n}{summary}\PY{p}{(}\PY{p}{)}
\end{Verbatim}
\end{tcolorbox}
\begin{tcolorbox}[breakable, size=fbox, boxrule=1pt, pad at break*=1mm,colback=cellbackground, colframe=cellborder]
\prompt{In}{incolor}{ }{\boxspacing}
\begin{Verbatim}[commandchars=\\\{\}]
\PY{n}{train\PYZus{}datagen} \PY{o}{=} \PY{n}{ImageDataGenerator}\PY{p}{(}\PY{n}{validation\PYZus{}split}\PY{o}{=}\PY{l+m+mf}{0.2}\PY{p}{,} \PY{n}{preprocessing\PYZus{}function}\PY{o}{=}\PY{n}{preprocess\PYZus{}input}\PY{p}{)} \PY{c+c1}{\PYZsh{} set validation split}
\end{Verbatim}
\end{tcolorbox}
\begin{tcolorbox}[breakable, size=fbox, boxrule=1pt, pad at break*=1mm,colback=cellbackground, colframe=cellborder]
\prompt{In}{incolor}{ }{\boxspacing}
\begin{Verbatim}[commandchars=\\\{\}]
\PY{c+c1}{\PYZsh{}Defines the batch\PYZhy{}size and keras generators}
\PY{n}{batch\PYZus{}size} \PY{o}{=} \PY{l+m+mi}{32}
\PY{n}{train\PYZus{}data\PYZus{}dir} \PY{o}{=} \PY{l+s+s1}{\PYZsq{}}\PY{l+s+s1}{Dataset/flower\PYZus{}photos/all}\PY{l+s+s1}{\PYZsq{}}
\PY{n}{train\PYZus{}generator} \PY{o}{=} \PY{n}{train\PYZus{}datagen}\PY{o}{.}\PY{n}{flow\PYZus{}from\PYZus{}directory}\PY{p}{(}
\PY{n}{train\PYZus{}data\PYZus{}dir}\PY{p}{,}
\PY{n}{target\PYZus{}size}\PY{o}{=}\PY{p}{(}\PY{n}{w}\PY{p}{,}\PY{n}{h}\PY{p}{)}\PY{p}{,}
\PY{n}{batch\PYZus{}size}\PY{o}{=}\PY{n}{batch\PYZus{}size}\PY{p}{,}
\PY{n}{class\PYZus{}mode}\PY{o}{=}\PY{l+s+s1}{\PYZsq{}}\PY{l+s+s1}{categorical}\PY{l+s+s1}{\PYZsq{}}\PY{p}{,}
\PY{n}{shuffle}\PY{o}{=}\PY{k+kc}{True}\PY{p}{,} \PY{n}{seed}\PY{o}{=}\PY{l+m+mi}{42}\PY{p}{,}
\PY{n}{subset}\PY{o}{=}\PY{l+s+s1}{\PYZsq{}}\PY{l+s+s1}{training}\PY{l+s+s1}{\PYZsq{}}\PY{p}{)} \PY{c+c1}{\PYZsh{} set as training data}
\PY{n}{val\PYZus{}generator} \PY{o}{=} \PY{n}{train\PYZus{}datagen}\PY{o}{.}\PY{n}{flow\PYZus{}from\PYZus{}directory}\PY{p}{(}
\PY{n}{train\PYZus{}data\PYZus{}dir}\PY{p}{,} \PY{c+c1}{\PYZsh{} same directory as training data}
\PY{n}{target\PYZus{}size}\PY{o}{=}\PY{p}{(}\PY{n}{w}\PY{p}{,}\PY{n}{h}\PY{p}{)}\PY{p}{,}
\PY{n}{batch\PYZus{}size}\PY{o}{=}\PY{n}{batch\PYZus{}size}\PY{p}{,}
\PY{n}{class\PYZus{}mode}\PY{o}{=}\PY{l+s+s1}{\PYZsq{}}\PY{l+s+s1}{categorical}\PY{l+s+s1}{\PYZsq{}}\PY{p}{,}
\PY{n}{shuffle}\PY{o}{=}\PY{k+kc}{True}\PY{p}{,} \PY{n}{seed}\PY{o}{=}\PY{l+m+mi}{42}\PY{p}{,}
\PY{n}{subset}\PY{o}{=}\PY{l+s+s1}{\PYZsq{}}\PY{l+s+s1}{validation}\PY{l+s+s1}{\PYZsq{}}\PY{p}{)} \PY{c+c1}{\PYZsh{} set as validation data}
\end{Verbatim}
\end{tcolorbox}
\begin{tcolorbox}[breakable, size=fbox, boxrule=1pt, pad at break*=1mm,colback=cellbackground, colframe=cellborder]
\prompt{In}{incolor}{ }{\boxspacing}
\begin{Verbatim}[commandchars=\\\{\}]
\PY{c+c1}{\PYZsh{} Gets the total number of images in dataset}
\PY{n}{filenames} \PY{o}{=} \PY{n}{train\PYZus{}generator}\PY{o}{.}\PY{n}{filenames}
\PY{n}{samples} \PY{o}{=} \PY{n+nb}{len}\PY{p}{(}\PY{n}{filenames}\PY{p}{)}
\PY{n+nb}{print}\PY{p}{(}\PY{n}{samples}\PY{p}{)}
\end{Verbatim}
\end{tcolorbox}
\begin{tcolorbox}[breakable, size=fbox, boxrule=1pt, pad at break*=1mm,colback=cellbackground, colframe=cellborder]
\prompt{In}{incolor}{ }{\boxspacing}
\begin{Verbatim}[commandchars=\\\{\}]
\PY{c+c1}{\PYZsh{} Defines Early Stopping and sabe the best model during training before overfitting.}
\PY{n}{file\PYZus{}name} \PY{o}{=} \PY{l+s+s1}{\PYZsq{}}\PY{l+s+s1}{best\PYZus{}model.h5}\PY{l+s+s1}{\PYZsq{}}
\PY{n}{checkpointer} \PY{o}{=} \PY{n}{ModelCheckpoint}\PY{p}{(}\PY{n}{file\PYZus{}name}\PY{p}{,} \PY{n}{monitor}\PY{o}{=}\PY{l+s+s1}{\PYZsq{}}\PY{l+s+s1}{val\PYZus{}accuracy}\PY{l+s+s1}{\PYZsq{}}\PY{p}{,} \PY{n}{save\PYZus{}best\PYZus{}only}\PY{o}{=}\PY{k+kc}{True}\PY{p}{)}
\PY{n}{early\PYZus{}stop} \PY{o}{=} \PY{n}{EarlyStopping}\PY{p}{(}\PY{n}{monitor} \PY{o}{=} \PY{l+s+s1}{\PYZsq{}}\PY{l+s+s1}{val\PYZus{}accuracy}\PY{l+s+s1}{\PYZsq{}}\PY{p}{,} \PY{n}{min\PYZus{}delta} \PY{o}{=} \PY{l+m+mf}{0.001}\PY{p}{,}
\PY{n}{mode} \PY{o}{=} \PY{l+s+s1}{\PYZsq{}}\PY{l+s+s1}{max}\PY{l+s+s1}{\PYZsq{}}\PY{p}{,} \PY{n}{patience} \PY{o}{=} \PY{l+m+mi}{10}\PY{p}{)}
\PY{n}{callbacks}\PY{o}{=}\PY{p}{[}\PY{n}{checkpointer}\PY{p}{,}\PY{n}{early\PYZus{}stop}\PY{p}{]}
\end{Verbatim}
\end{tcolorbox}
\begin{tcolorbox}[breakable, size=fbox, boxrule=1pt, pad at break*=1mm,colback=cellbackground, colframe=cellborder]
\prompt{In}{incolor}{ }{\boxspacing}
\begin{Verbatim}[commandchars=\\\{\}]
\PY{c+c1}{\PYZsh{} Defines number of epochs and train the model}
\PY{n}{epochs} \PY{o}{=} \PY{l+m+mi}{100}
\PY{n}{steps\PYZus{}in\PYZus{}epoch} \PY{o}{=} \PY{n}{samples} \PY{o}{/}\PY{o}{/} \PY{n}{batch\PYZus{}size}
\PY{n}{history} \PY{o}{=} \PY{n}{custom\PYZus{}resnet}\PY{o}{.}\PY{n}{fit\PYZus{}generator}\PY{p}{(}\PY{n}{train\PYZus{}generator}\PY{p}{,} \PY{n}{steps\PYZus{}per\PYZus{}epoch}\PY{o}{=}\PY{n}{steps\PYZus{}in\PYZus{}epoch}\PY{p}{,} \PY{n}{epochs}\PY{o}{=}\PY{n}{epochs}\PY{p}{,}
\PY{n}{validation\PYZus{}data}\PY{o}{=}\PY{n}{val\PYZus{}generator}\PY{p}{,} \PY{n}{validation\PYZus{}steps}\PY{o}{=}\PY{l+m+mi}{1}\PY{p}{,}
\PY{n}{verbose}\PY{o}{=}\PY{l+m+mi}{1}\PY{p}{,}\PY{n}{callbacks}\PY{o}{=}\PY{n}{callbacks}\PY{p}{)}
\end{Verbatim}
\end{tcolorbox}
\begin{tcolorbox}[breakable, size=fbox, boxrule=1pt, pad at break*=1mm,colback=cellbackground, colframe=cellborder]
\prompt{In}{incolor}{ }{\boxspacing}
\begin{Verbatim}[commandchars=\\\{\}]
\PY{k}{def} \PY{n+nf}{graph\PYZus{}training\PYZus{}history}\PY{p}{(}\PY{n}{history}\PY{p}{)}\PY{p}{:}
\PY{n}{acc\PYZus{}train} \PY{o}{=} \PY{n}{history}\PY{p}{[}\PY{l+s+s1}{\PYZsq{}}\PY{l+s+s1}{accuracy}\PY{l+s+s1}{\PYZsq{}}\PY{p}{]}
\PY{n}{acc\PYZus{}test} \PY{o}{=} \PY{n}{history}\PY{p}{[}\PY{l+s+s1}{\PYZsq{}}\PY{l+s+s1}{val\PYZus{}accuracy}\PY{l+s+s1}{\PYZsq{}}\PY{p}{]}
\PY{n}{loss\PYZus{}train} \PY{o}{=} \PY{n}{history}\PY{p}{[}\PY{l+s+s1}{\PYZsq{}}\PY{l+s+s1}{loss}\PY{l+s+s1}{\PYZsq{}}\PY{p}{]}
\PY{n}{loss\PYZus{}test} \PY{o}{=} \PY{n}{history}\PY{p}{[}\PY{l+s+s1}{\PYZsq{}}\PY{l+s+s1}{val\PYZus{}loss}\PY{l+s+s1}{\PYZsq{}}\PY{p}{]}
\PY{n}{plt}\PY{o}{.}\PY{n}{rcParams}\PY{p}{[}\PY{l+s+s1}{\PYZsq{}}\PY{l+s+s1}{axes.facecolor}\PY{l+s+s1}{\PYZsq{}}\PY{p}{]}\PY{o}{=}\PY{l+s+s1}{\PYZsq{}}\PY{l+s+s1}{white}\PY{l+s+s1}{\PYZsq{}}
\PY{n}{fig} \PY{o}{=} \PY{n}{plt}\PY{o}{.}\PY{n}{figure}\PY{p}{(}\PY{l+m+mi}{1}\PY{p}{)}
\PY{c+c1}{\PYZsh{} summarize history for accuracy}
\PY{n}{plt}\PY{o}{.}\PY{n}{subplot}\PY{p}{(}\PY{l+m+mi}{121}\PY{p}{)}
\PY{n}{plt}\PY{o}{.}\PY{n}{plot}\PY{p}{(}\PY{n}{acc\PYZus{}train}\PY{p}{)}
\PY{n}{plt}\PY{o}{.}\PY{n}{plot}\PY{p}{(}\PY{n}{acc\PYZus{}test}\PY{p}{)}
\PY{n}{plt}\PY{o}{.}\PY{n}{title}\PY{p}{(}\PY{l+s+s1}{\PYZsq{}}\PY{l+s+s1}{model accuracy}\PY{l+s+s1}{\PYZsq{}}\PY{p}{)}
\PY{n}{plt}\PY{o}{.}\PY{n}{ylabel}\PY{p}{(}\PY{l+s+s1}{\PYZsq{}}\PY{l+s+s1}{accuracy}\PY{l+s+s1}{\PYZsq{}}\PY{p}{)}
\PY{n}{plt}\PY{o}{.}\PY{n}{xlabel}\PY{p}{(}\PY{l+s+s1}{\PYZsq{}}\PY{l+s+s1}{epoch}\PY{l+s+s1}{\PYZsq{}}\PY{p}{)}
\PY{n}{plt}\PY{o}{.}\PY{n}{legend}\PY{p}{(}\PY{p}{[}\PY{l+s+s1}{\PYZsq{}}\PY{l+s+s1}{train}\PY{l+s+s1}{\PYZsq{}}\PY{p}{,} \PY{l+s+s1}{\PYZsq{}}\PY{l+s+s1}{test}\PY{l+s+s1}{\PYZsq{}}\PY{p}{]}\PY{p}{,} \PY{n}{loc}\PY{o}{=}\PY{l+s+s1}{\PYZsq{}}\PY{l+s+s1}{upper left}\PY{l+s+s1}{\PYZsq{}}\PY{p}{)}
\PY{n}{plt}\PY{o}{.}\PY{n}{tight\PYZus{}layout}\PY{p}{(}\PY{p}{)}
\PY{c+c1}{\PYZsh{} summarize history for loss}
\PY{n}{plt}\PY{o}{.}\PY{n}{subplot}\PY{p}{(}\PY{l+m+mi}{122}\PY{p}{)}
\PY{n}{plt}\PY{o}{.}\PY{n}{plot}\PY{p}{(}\PY{n}{loss\PYZus{}train}\PY{p}{)}
\PY{n}{plt}\PY{o}{.}\PY{n}{plot}\PY{p}{(}\PY{n}{loss\PYZus{}test}\PY{p}{)}
\PY{n}{plt}\PY{o}{.}\PY{n}{title}\PY{p}{(}\PY{l+s+s1}{\PYZsq{}}\PY{l+s+s1}{model loss}\PY{l+s+s1}{\PYZsq{}}\PY{p}{)}
\PY{n}{plt}\PY{o}{.}\PY{n}{ylabel}\PY{p}{(}\PY{l+s+s1}{\PYZsq{}}\PY{l+s+s1}{loss}\PY{l+s+s1}{\PYZsq{}}\PY{p}{)}
\PY{n}{plt}\PY{o}{.}\PY{n}{xlabel}\PY{p}{(}\PY{l+s+s1}{\PYZsq{}}\PY{l+s+s1}{epoch}\PY{l+s+s1}{\PYZsq{}}\PY{p}{)}
\PY{n}{plt}\PY{o}{.}\PY{n}{legend}\PY{p}{(}\PY{p}{[}\PY{l+s+s1}{\PYZsq{}}\PY{l+s+s1}{train}\PY{l+s+s1}{\PYZsq{}}\PY{p}{,} \PY{l+s+s1}{\PYZsq{}}\PY{l+s+s1}{test}\PY{l+s+s1}{\PYZsq{}}\PY{p}{]}\PY{p}{,} \PY{n}{loc}\PY{o}{=}\PY{l+s+s1}{\PYZsq{}}\PY{l+s+s1}{upper right}\PY{l+s+s1}{\PYZsq{}}\PY{p}{)}
\PY{n}{plt}\PY{o}{.}\PY{n}{tight\PYZus{}layout}\PY{p}{(}\PY{p}{)}
\PY{n}{plt}\PY{o}{.}\PY{n}{show}\PY{p}{(}\PY{p}{)}
\PY{n}{fig}\PY{o}{.}\PY{n}{savefig}\PY{p}{(}\PY{l+s+s1}{\PYZsq{}}\PY{l+s+s1}{weights/history.png}\PY{l+s+s1}{\PYZsq{}}\PY{p}{,} \PY{n}{dpi}\PY{o}{=}\PY{n}{fig}\PY{o}{.}\PY{n}{dpi}\PY{p}{)}
\end{Verbatim}
\end{tcolorbox}
\begin{tcolorbox}[breakable, size=fbox, boxrule=1pt, pad at break*=1mm,colback=cellbackground, colframe=cellborder]
\prompt{In}{incolor}{ }{\boxspacing}
\begin{Verbatim}[commandchars=\\\{\}]
\PY{n}{graph\PYZus{}training\PYZus{}history}\PY{p}{(}\PY{n}{history}\PY{o}{.}\PY{n}{history}\PY{p}{)}
\end{Verbatim}
\end{tcolorbox}
\begin{tcolorbox}[breakable, size=fbox, boxrule=1pt, pad at break*=1mm,colback=cellbackground, colframe=cellborder]
\prompt{In}{incolor}{ }{\boxspacing}
\begin{Verbatim}[commandchars=\\\{\}]
\PY{c+c1}{\PYZsh{} Saving history}
\PY{k}{with} \PY{n+nb}{open}\PY{p}{(}\PY{l+s+s1}{\PYZsq{}}\PY{l+s+s1}{weights/history\PYZus{}model.json}\PY{l+s+s1}{\PYZsq{}}\PY{p}{,} \PY{l+s+s1}{\PYZsq{}}\PY{l+s+s1}{w}\PY{l+s+s1}{\PYZsq{}}\PY{p}{)} \PY{k}{as} \PY{n}{f}\PY{p}{:}
\PY{n}{json}\PY{o}{.}\PY{n}{dump}\PY{p}{(}\PY{n+nb}{str}\PY{p}{(}\PY{n}{custom\PYZus{}resnet}\PY{o}{.}\PY{n}{history}\PY{o}{.}\PY{n}{history}\PY{p}{)}\PY{p}{,} \PY{n}{f}\PY{p}{)}
\end{Verbatim}
\end{tcolorbox}
\begin{tcolorbox}[breakable, size=fbox, boxrule=1pt, pad at break*=1mm,colback=cellbackground, colframe=cellborder]
\prompt{In}{incolor}{ }{\boxspacing}
\begin{Verbatim}[commandchars=\\\{\}]
\end{Verbatim}
\end{tcolorbox}
% Add a bibliography block to the postdoc
\end{document}